A Built-in Methodology for Resemblance Gathering in RKII Networks

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2007

Autores

Cândido Duarte (Autor) FEUP; Vítor Grade Tavares (Autor) FEUP; José Machado da Silva (Autor) FEUP; Sebastian Tabarce (Autor) FEUP

Ata de Conferência Internacional

Título: 13th International Mixed Signals Testing Workshop and 3rd GHz/Gbps Test Workshop (IMSTW / GTW 2007)

Páginas: 57-60

13th International Mixed Signals Testing Workshop and 3rd GHz/Gbps Test Workshop (IMSTW / GTW 2007)

Póvoa de Varzim, Portugal, 18-20 June

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Engenharia electrotécnica, electrónica e informática

CORDIS: Ciências Tecnológicas > Engenharia > Engenharia electrotécnica

Outras Informações

Abstract (EN): This paper presents a methodology to test RKII cells for dynamic resemblance.The cells are the basic processing blocks of RKII networks, which, as with other Artificial Neural Networks, are made of repeated processing elements interconnected in some pre-defined manner. For the RKII network, each processing element, the RKII, is a dynamic piece that behaves as an input controlled oscillator, therefore the network represents a set of coupled oscillators. Each RKII cell in the network should exhibit similar characteristics for suitable operation. However, in a real analogue CMOS VLSI implementation, similarity will change along the integrated circuit, due to process variations, failures, or even performance degradation. The variations found in different cells may prevent the network to operate properly. The present work presents a method to find and select a set of RKII cells, within the chip universe, that reflects a pre-defined degree of similitude. The method employs an iterative procedure that searches the network to find the set of cells that fit within a percentage of dynamic variation, and finds a maximum number of cells that best resemble each other. In the end, the most similar cells are selected while the others are turned off.

Idioma: Português

Tipo (Avaliação Docente): Científica